Wingbits AI is a platform that enables users to create AI agents for real-time monitoring of aircraft activity and receive alerts based on specific criteria. It is built on top of a proprietary global network of over 5,600 antennas across 120 countries, which generates terabytes of data daily from ADS-B signals. The main purpose is to allow users to extract insights from aviation data without needing a data science team or complex infrastructure. Key features include the ability to ask questions in plain English about current flights, such as "where is Air Force One right now?" or "Which private jets visited Davos last weekend?". Users can create agents that monitor for specific events like military aircraft in a region, private or government jets, GPS-jamming spikes, or tracking friends and family. These agents can send alerts to destinations like Slack, email, Telegram, or Teams the moment something relevant happens. The platform also provides scheduled reports or analysis on topics like competitor routes and can compare GPS jamming events across regions. The platform works by processing clean, deduplicated data from its real-time stream that ingests approximately 3TB of data daily with under 1-second latency. Agents query this cleaned data and can be configured with evaluation cadence and time windows. They have access to their own alert history to decide if enough has changed to warrant a new alert, helping to reduce alert fatigue. The system is designed to provide fewer, higher-confidence alerts by integrating context from other data sources like NOTAMs and weather alerts to interpret deviations. Benefits include gaining geopolitical or operational insights from aviation data without requiring coding, data processing, or managing infrastructure. Use cases are for reporters tracking unusual military activity, prediction markets, competitive analysts monitoring competitor routes, route planners, and aviation enthusiasts. It helps users monitor pattern shifts like unusual route behavior, repeated delays, or sudden volume changes that suggest a change from a normal baseline. The target users are reporters, prediction markets, competitive analysts, route planners, and aviation enthusiasts. The platform is built with technologies indicated by the "Built with" section including Framer, Linear, and Claude by Anthropic. It offers a no-code experience and is accessible via a web platform. The underlying data network is transparent about coverage quality, which is denser in regions like the US and Europe and growing in Latin America, Asia, and the Middle East.